Fast image restoration for blurred remote sensing image is one of the focus problem in optical image processing. We present a method for remote sensing image restoration using a gyroscope sensor mounted with the camera. With motion track of the camera obtained from gyroscope sensor, we get a better PSF(Point Spread Function) estimation by calibrating the camera. Then we use the TV regularization to solve this non-blind deconvolution which runs faster than blind deconvolution. In experiments, we established a platform to simulate the vibration of satellite and get the synchronized gyroscope data in the exposure time, then we compare our restoration results with ground truth. Our experiments show that, the method has a good performance for blurred image caused by vibration of image system.
A novel over exposure (OE) correction method using Dark Channel Prior and image fusion technique is proposed in this work. Assuming an OE image can be modeled as a normal exposure image added up with a layer of asymmetrical haze, its submerged information in OE regions is enhanced by haze removal model. With image fusion technique, the obtained texture in OE regions is used to restore the over exposure. Experiments show that our method works well in submerged information restoration without increasing pseudo-information and over Saturation.